9711cb56111546aeed1be4b2c0ba1738080c848c lrnassar Tue Jul 28 17:31:52 2026 -0700 Fix "basepair" wording and Methods punctuation on the Deleteriousness Predictions description pages per QA feedback. refs #37510 Changes "basepair" to "base" in the shared zoom-in instructions on clinPred, revel, alphaMissense, caddSuper, and caddSuper1_7, and normalizes predictionScoresSuper from "base pair" to "base" so the container is consistent. Removes an awkward comma in the source-repository sentence on clinPred and revel. Switches the hgdownload links on the clinPred page to https to match the other links on that page. diff --git src/hg/makeDb/trackDb/human/clinPred.html src/hg/makeDb/trackDb/human/clinPred.html index c24f8529d37..a49c91e1b46 100644 --- src/hg/makeDb/trackDb/human/clinPred.html +++ src/hg/makeDb/trackDb/human/clinPred.html @@ -1,126 +1,126 @@
This track collection shows ClinPred scores, a machine-learning predictor of pathogenicity for nonsynonymous (missense) single-nucleotide variants. ClinPred combines existing pathogenicity scores with population allele frequency from gnomAD, and was trained on confidently annotated disease-causing and benign variants from ClinVar. Pre-computed scores are provided for all possible human missense variants in the exome.
Scores range from 0 to 1, with higher values indicating greater predicted likelihood that a variant is disease-relevant. The authors recommend a score of ≥ 0.5 as evidence of pathogenicity. As with any pathogenicity prediction score, ClinPred is intended as supporting evidence rather than a stand-alone classifier.
There are four subtracks in this collection, one for each possible alternate nucleotide. At every exome position covered by ClinPred, three of the four subtracks show a score (one per non-reference base) and the fourth, corresponding to the reference base, is set to 0. Synonymous alternates, those that do not change the encoded amino acid, are also set to 0, since ClinPred only scores missense variants. Positions with no exome coverage are shown as gaps.
-When using this track, zoom in until you can see every basepair at the top of +When using this track, zoom in until you can see every base at the top of the display. Otherwise, several nucleotides fall under each pixel and no score will be shown on the mouseover tooltip.
Track colors
Each subtrack is colored by score using the threshold recommended by the ClinPred authors:
| Range | Classification |
|---|---|
| ≥ 0.5 | Likely pathogenic |
| < 0.5 | Likely benign |
ClinPred scores are available at the ClinPred website, which provides pre-computed scores for all possible human missense variants.
The ClinPred data on the UCSC Genome Browser can be explored interactively with
the Table Browser or the
Data Integrator. For automated download
and analysis, the data are stored in bigWig files and can be downloaded from
-our
+our
download server. The files are named a.bw, c.bw, g.bw, t.bw.
Individual regions can be obtained using bigWigToBedGraph, which can
be compiled from source or downloaded as a precompiled binary; instructions
-are here.
+are here.
For example:
-bigWigToBedGraph -chrom=chr1 -start=100000 -end=100500 http://hgdownload.soe.ucsc.edu/gbdb/$db/clinPred/a.bw stdout
+bigWigToBedGraph -chrom=chr1 -start=100000 -end=100500 https://hgdownload.soe.ucsc.edu/gbdb/$db/clinPred/a.bw stdout
Data were downloaded from the ClinPred website on May 5, 2026, and converted into four per-alternate-base bigWig files using a custom script. As with all other tracks, a full log of the commands used for the conversion is available in our -source repository, for +source repository for hg19 and hg38.
ClinPred scores are freely available for non-commercial applications. For commercial use, please see the licensing information on the ClinPred website.
Thanks to the ClinPred authors for making the pre-computed scores available through their website.
Alirezaie N, Kernohan KD, Hartley T, Majewski J, Hocking TD. ClinPred: Prediction Tool to Identify Disease-Relevant Nonsynonymous Single-Nucleotide Variants. Am J Hum Genet. 2018 Oct 4;103(4):474-483. PMID: 30220433; PMC: PMC6174354